The human eye is made up of three coats, or layers, enclosing three transparent structures. The outermost layer is composed of the cornea and sclera. The middle layer consists of the choroid, ciliary body, and iris. The innermost coat is the retina, which gets its circulation from the vessels of the choroid as well as the retinal vessels. The retina is a light-sensitive layer at the back of the eye that covers about 65 percent of its interior surface. The human eye contains two kinds of photoreceptor cells; rods and cones. These photoreceptor cells are photosensitive and convert incident light energy into signals that are carried to the brain by the optic nerve.
In the middle of the retina is a small dimple called the fovea (also known as the fovea centralis). The fovea is the center of the eye's sharpest vision and the location of most color perception; it is responsible for providing the brain with detailed image information, necessary for precise recognition of objects and shapes used in activities such as reading, driving and operating machinery. In most individuals, the fovea covers about 2 degrees of visual angle. In concentric fashion, the parafovea, perifovea and peripheral regions surround the fovea and provide increasingly diminished resolution. To get a clear view of the world, the brain must turn the eyes so that the image of the object of regard falls on the fovea. Eye movements are thus very important for visual perception, and any failure to make them correctly can lead to serious visual issues.
Foveal imaging (also known as space variant imaging or gaze contingent imaging) is a digital image processing technique where the image resolution, or amount of detail, varies across the image, in a manner similar to that of the human eye, according to one or more so-called “fixation points.” Generally, a fixation point designates the highest resolution region of a given image and corresponds to the center of the eye's retina (i.e., the fovea). Depending on the image processing being used, fixation point location can be specified in different ways. For example, in some environments, a pointing device, such as a computer mouse, can specify a fixing point within an image displayed on a computer monitor. In other environments, computer algorithms also can automatically determine fixation points in images.
In some embodiments, the location and type of a fixation point can vary depending on the application in which the method, device, or system is being used. For example, in one embodiment, an application can have a static fixation point (like the crosshair examples described herein). In another embodiment, an application can have a dynamic fixation point (one illustrative example of such an application is a facial recognition application, such as facial recognition software running on a video stream looking at a crowd of people but wanting only to process the data from the faces). Before the current frame is digitized (i.e., before power is consumed), it is advantageous, in at least some embodiment, to recognize, determine, or even predetermine, which paxels to spend power on to increase ENoB for those paxels. This selective selection of preferred paxels on which to spend power has advantages over approaches that digitize most or all of an entire frame at or close to maximum ENoB. For example, if an entire image frame is digitized at maximum ENoB, and the result is later foveated, there is much less opportunity (perhaps no opportunity) to reduce power consumption of the ADC.
In still further environments such as human perception experiments, devices can be used to measure the position and movement of a human eye (e.g., eye tracker devices). Eye trackers, which can be used to manipulate an image on a computer display, also can be used to determine fixation points. Eye tracking, as is known in the art, is the process of measuring either the point of gaze (where one is looking) or the motion of an eye relative to the head. A display able to be manipulated via eye tracker is known as a gaze contingent display. Gaze-Contingent Displays (GCDs) attempt to balance the amount of information displayed against the visual information processing capacity of the observer through real-time eye movement sensing.